Kelp vs Urchins
Nick Toimieri
sys.date()
1 Triggers and settings
2 Import Data
Note: for Neah Bay in 2016
- There are not algae data for the South Area only, the North.
- There are are only two transects of invert data for the North. There are 5 transects in the South area.
3 By KELP SPECIES but summed across all urchins
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.1 Individual plot version
The following splits the facet into individual plots for better plotting and labeling.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.2 Site x Year regressions for urchins vs kelp
##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Tatoosh Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2240 -0.4312 -0.2485 0.5608 1.4392
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2614 0.6582 1.916 0.104
## Urchins 0.2176 0.4320 0.504 0.632
##
## Residual standard error: 0.9187 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.04058, Adjusted R-squared: -0.1193
## F-statistic: 0.2538 on 1 and 6 DF, p-value: 0.6324##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Destruction Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7381 -0.6178 0.1280 0.4375 0.7938
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.8137 0.2701 3.013 0.0236 *
## Urchins -0.2925 0.9198 -0.318 0.7612
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6494 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.01658, Adjusted R-squared: -0.1473
## F-statistic: 0.1011 on 1 and 6 DF, p-value: 0.7612##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Tatoosh Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6070 -0.3621 -0.1145 0.2932 0.9539
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4419 0.3984 1.109 0.3098
## Urchins 0.8263 0.2615 3.161 0.0196 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.556 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.6247, Adjusted R-squared: 0.5622
## F-statistic: 9.989 on 1 and 6 DF, p-value: 0.01955##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Destruction Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.29180 -0.09352 0.02426 0.11111 0.20435
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.51085 0.07857 6.502 0.00063 ***
## Urchins -0.15486 0.26756 -0.579 0.58379
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1889 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.05288, Adjusted R-squared: -0.105
## F-statistic: 0.335 on 1 and 6 DF, p-value: 0.58384 Total for each.
I know we’re not supposed to combine macro & nereo but…just to see
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site'. You can override using the
## `.groups` argument.
5 BY SPECIES
5.1 Transect level, all depths
##
## Attaching package: 'cowplot'## The following object is masked from 'package:ggpubr':
##
## get_legend## The following object is masked from 'package:lubridate':
##
## stamp## Loading required package: viridisLite
## By Site and Depth level
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 1020 7## [1] 340 5## [1] 255 5
correlation purple vs nereo at Tatoosh r = 0.2147361, p = 0.0484337
5.2 By Site and 5 m only
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 1020 7## [1] 340 5## [1] 255 5## $x
## [1] "Urchin density"
##
## $y
## [1] "Kelp density"
##
## $colour
## [1] "Site"
##
## attr(,"class")
## [1] "labels"
5.3 By site, averaged across depths, data = years
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.## [1] 540 7## [1] 180 4## [1] 135 4
## [1] NA## [1] NAThis plot compared to the previous is interesting.
At the transect level, there is a negative correlation between urchin density and kelp neroycystis density at Tatoosh
At the site level, there is a positive correlation for Nerocystis (r = NA) and for Pterogophora (r = NA)at Tatoosh across years.
6 TATOOSH
6.1 By transect
##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.9829 0.3557 5.575 2.93e-07 ***
## k -0.1109 0.0717 -1.547 0.126
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.935 on 84 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 3.406e-06## a k
## 1.9829546 -0.1109077## [1] 361.5355
7 Across years
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8 Coastwide urchin - kelp patterns
8.1 All kelp: Nereo + Macro + Ptero
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor: r = 0.7456971; p = 0.0210725
8.2 Canopy only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.534885
8.3 Nero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8.4 Macro only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Ptero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.7032538; = 0.034552
9 Tatoosh only
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.33515 0.16320 8.181 2.63e-12 ***
## k -0.13208 0.08223 -1.606 0.112
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9816 on 84 degrees of freedom
##
## Number of iterations to convergence: 4
## Achieved convergence tolerance: 5.016e-06## a k
## 1.3351476 -0.1320835## [1] 244.8431
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.60569 0.26098 6.153 2.49e-08 ***
## k -0.01246 0.07727 -0.161 0.872
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.776 on 84 degrees of freedom
##
## Number of iterations to convergence: 4
## Achieved convergence tolerance: 3.804e-06## a k
## 1.60569036 -0.01245511## [1] 346.7817
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.9070 0.3590 5.312 8.73e-07 ***
## k -0.2230 0.1577 -1.414 0.161
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.984 on 84 degrees of freedom
##
## Number of iterations to convergence: 10
## Achieved convergence tolerance: 4.821e-06## a k
## 1.9070384 -0.2230188## [1] 365.9036
10 Combined Figure 5
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
##
## Attaching package: 'gridExtra'
##
##
## The following object is masked from 'package:dplyr':
##
## combine
##
##
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
11 Kelp vs Kelp
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
Correlations between kelps
Macro vs Nereocystis, all sites r = -0.3779968 with p = 0.0104645
Macro vs Nereocystis, two sites r = 0.0648126 with p = 0.798334
Macro vs Pterygophora, all sites r = 0.1636673 with p = 0.2826962
Macro vs Nereocystis, all sites r = 0.1209657 with p = 0.4286285
12 Correlations at Tatoosh Island across years (yearly means) for different depth zones
A different, and simplified version of the above for just tatoosh and faceted by species.
Essentially, there are different relationships at different depths. Probably too much detail for this manuscript.
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone'. You can override
## using the `.groups` argument.